Parking availability monitor for a non-demarcated parking zone

ABSTRACT

An example method described herein includes receiving an image stream of a non-demarcated parking zone; identifying dimensions of the non-demarcated parking zone; determining an overall area of the non-demarcated parking zone based on the dimensions of the non-demarcated parking zone; calculating a capacity of the non-demarcated parking zone based on the dimensions of the overall area and predetermined vehicle dimensions; determining a number of vehicles parked in the non-demarcated parking zone based on the image stream and an object detection model, wherein the object detection model is configured to detect vehicles in the image stream that are parked in the non-demarcated parking zone; determining a parking availability of the non-demarcated parking zone based on the number of vehicles parked in the non-demarcated parking zone and the capacity; and performing an action associated with the parking availability.

RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.16/202,824, filed Nov. 28, 2018, which is incorporated herein byreference.

BACKGROUND

A parking zone is an area that is designated or intended for vehicleparking. A parking zone can be situated in urban areas and/or ruralareas along streets and/or near destinations such as, places ofbusiness, recreational areas, industrial parks, churches, schools,and/or other similar venues. In some instances, a parking zone caninclude one or more security devices (e.g., cameras, sensors, and/or thelike) that monitor vehicle parking and/or authorize vehicle access tothe parking zone (e.g., via a payment transaction, via an access card,and/or the like).

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A-1C are diagrams of an example implementation described herein.

FIG. 2 is a diagram of an example implementation described herein.

FIG. 3 is a diagram of an example implementation described herein.

FIG. 4 is a diagram of an example environment in which systems and/ormethods, described herein, can be implemented.

FIG. 5 is a diagram of example components of one or more devices of FIG.4.

FIG. 6 is a flow chart of an example process associated with a parkingavailability monitor for a non-demarcated parking zone.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

The following detailed description of example implementations refers tothe accompanying drawings. The same reference numbers in differentdrawings can identify the same or similar elements.

Depending on a location of a parking zone and/or a time of the day, theparking zone can be very busy and can potentially be at or nearcapacity. Accordingly, in many instances, a driver can spend an extendedperiod of time trying to find available parking within the parking zone.During that extended period of time, the driver can travel in a vehiclethroughout the parking zone and/or along parking zones that are on thestreets, seeking available parking locations. Such time and travel canwaste valuable resources of the driver and/or the vehicle. In someinstances, when parking zones include demarcated parking spots (e.g.,allocated and/or marked locations or spaces of a parking zone where thevehicle can be parked), a parking system and/or application can beavailable to indicate available parking of a particular parking zone.The parking system and/or application can use markings (e.g., paintedlines, signs, markers, reflectors, and/or the like) to identify theparking spots in the parking zone. Accordingly, if a vehicle is detectedwithin or near the markings of a parking spot, the parking system and/orapplication can determine that the parking spot is occupied and if novehicle is detected within or near the markings of the parking spot, theparking system and/or application can determine that the parking spot isvacant or available.

However, a parking zone might not include markings to allocate specificlocations intended for individual vehicles. Such a parking zone isreferred to herein as a non-demarcated parking zone. Although thenon-demarcated parking zone can be marked as a parking zone, thenon-demarcated parking zone does not include markings for individualparking spots for individual vehicles. A non-demarcated parking zone caninclude a street parking area along a curb or shoulder of a street, anon-demarcated parking lot, a temporary parking lot (e.g., parking lotscreated for specific lengths of time or events), such as a field orgrassy area, and/or the like. As such, for a non-demarcated parkingzone, previously available parking systems or applications cannotdetermine parking availability of the non-demarcated parking zonesbecause there are no markings to identify the allocated parkinglocations in the parking zones.

Some implementations herein provide a parking system that facilitatesidentifying and/or providing parking availability in non-demarcatedparking zones. For example, the parking system can monitor anon-demarcated parking zone (e.g., via an image stream from a camerafocused on the non-demarcated parking zone), determine a size of an areaof the non-demarcated parking zone, determine a size of an occupancyarea consumed by one or more vehicles, and calculate an available areaof the non-demarcated parking zone to determine whether there is anavailable parking space within the non-demarcated parking zone and/or aprobability that there is an available parking space within thenon-demarcated parking zone. In some implementations, the parking systemcan use historical data associated with the non-demarcated parking zoneto estimate and/or predict parking availability based on the historicaldata, characteristics of the non-demarcated parking zone, and/orcharacteristics of a vehicle that a driver is seeking to park in thenon-demarcated parking zone.

In some implementations, the parking system can identify and/or providea best available parking area of a non-demarcated parking zone and/or abest available parking zone of a plurality of non-demarcated parkingzones for a vehicle based on a destination associated with the vehicle.For example, the destination associated with the vehicle can be alocation indicated by an address entered in a global positioning system(GPS) of the vehicle or an address entered into a device associated withthe vehicle (e.g., via an application, such as a parking applicationused to communicate with the parking system, a navigation application, amap application, and/or the like). In such cases, the parking system cannavigate the driver to the best available parking area of thenon-demarcated parking zone.

Accordingly, examples herein can provide a parking system that enables avehicle and/or a driver of a vehicle to relatively quickly identifyavailable parking in a non-demarcated parking zone, thus saving user andvehicle resources (e.g., fuel, mileage, usage, maintenance, and/or thelike).

FIGS. 1A-1C are diagrams of an example implementation 100 describedherein. In example implementation 100, a parking system can identifyparking availability of a non-demarcated parking zone positioned alongan edge of a street. As shown in FIGS. 1A-1C, the non-demarcated parkingzone can include various numbers of vehicles, various types of vehicles,vehicles parked in various positions at different or various times. Asdescribed herein, the parking system can be configured to determine theparking availability at the various times based on the position and/ornumber of vehicles parked within the non-demarcated parking zone and acapacity of the non-demarcated parking zone. In some implementations,the parking availability can indicate whether there is availability fora vehicle to park in the non-demarcated parking zone and/or aprobability that the vehicle can park in the non-demarcated parkingzone.

As shown in FIG. 1A, and by reference number 110, a parking systemcaptures images of a non-demarcated parking zone. For example, camerasA-D can capture an image stream (e.g., a series or sequence of images,such as video) of vehicles parked in the non-demarcated parking zone.The image stream can be provided to a controller or processor of theparking system that is configured to analyze the image stream asdescribed herein. In some implementations, cameras A-D can continuouslyprovide the image stream (or video), can provide images or an imagestream periodically or at particular time intervals, and/or based ondetecting an event (e.g., a vehicle entering or leaving thenon-demarcated parking zone).

As further shown in FIG. 1A, and by reference number 120, the parkingsystem identifies the vehicles parked in the non-demarcated parking zoneat various times. For example, as shown in FIG. 1A, cameras A-D cancapture an image of three vehicles within the non-demarcated parkingzone at 22:00 on Sep. 25, 2018 and the system can detect the vehicles(e.g., using an object recognition technique, as described herein). Insome implementations, the parking system can utilize sensors, securitydevices, and/or the like to detect the presence of a vehicle in thenon-demarcated parking zone at the various times.

As shown in FIG. 1B, and by reference number 130, the parking systemdetermines a capacity of the non-demarcated parking zone. In someimplementations, the parking system can determine the capacity of thenon-demarcated parking zone based on tracking a maximum number ofvehicles detected within the non-demarcated parking zone over a timeperiod. For example, the parking system can determine the most vehiclesparked in the non-demarcated parking zone over a most recent time period(e.g., the most recent week, the most recent month, the most recentyear, and/or the like), over a calibration time period (e.g., a week, amonth, a year, and/or the like that the parking system monitored thenon-demarcated parking zone), and/or the like.

In some implementations, the parking system can determine the capacityof the non-demarcated parking zone based on a size of the non-demarcatedparking zone and a size (e.g., an average size and/or a default size) ofa vehicle. For example, an area of the non-demarcated parking zone canbe divided by an occupancy area of a vehicle plus some buffer area(e.g., a constant area) to allow for space between the parked vehiclesin the non-demarcated parking zone. The occupancy area (and/or bufferarea) can be calculated from predetermined dimensions of a vehicle. Insome implementations, the predetermined dimensions can correspond toaverage dimensions of a set of vehicles. In such cases, the set ofvehicles can be a set of vehicles that have been manufactured within athreshold time period (e.g., within the last year, with the last tenyears, within the last one hundred years, and/or the like), a set ofvehicles that are used in a geographic location of the non-demarcatedparking zone, a set of vehicles that are top-selling vehicles in ageographic location of the non-demarcated parking zone, and/or the like.Additionally, or alternatively, the set of vehicles can be a set ofvehicles that have parked in the non-demarcated parking zone over a pasttime period. For example, the parking system can analyze, using an imageanalysis (e.g., object recognition, object analysis, computer vision,and/or the like) of vehicles in images from the image stream, sizes(e.g., lengths) of the vehicles that have parked in the non-demarcatedparking zone over the last week, the last month, the last year, and/orthe like. The predetermined dimensions can include an average length ofthe vehicles that have parked in the non-demarcated parking zone overthat time period. As such, the parking system can be adaptable toparticular locations and/or demographic areas and, thus, more accuratein its calculations. For example, a non-demarcated parking zone in arural area can be more likely to include larger vehicles, such as pickuptrucks or work machines, while a non-demarcated parking zone in an urbanarea can be more likely to include smaller vehicles, such as sedans orcompact cars. Furthermore, using a set of vehicles that have parked inthe non-demarcated parking zone, the parking system can use anautomatically adjustable occupancy area to determine the capacity of thenon-demarcated parking zone. Furthermore, the parking system can bedeployed without any calibration, and can automatically determine acapacity of a particular non-demarcated parking zone based on the sizesof vehicles that are likely to be parked in the non-demarcated parkingzone.

The parking system can determine the size of the non-demarcated parkingzone based on one or more dimensions (e.g., length and/or width) of thenon-demarcated parking zone. For example, the parking system cancalculate the area using a determined length and width of thenon-demarcated parking zone. In some implementations, the parking systemcan determine the size of the non-demarcated parking zone from a singledimension. For example, for a non-demarcated parking zone along the sideof a road (as shown in implementation 100), the parking system candetermine the size of the non-demarcated parking zone based on thelength of the road, a distance between intersections of the road, and/orthe like. In some implementations, the parking system can identifynon-available parking areas of the non-demarcated parking zone. Forexample, there can be areas of the non-demarcated parking zone that arenear a fire hydrant, a driveway, an intersection, and/or the like. Theparking system can identify such areas using an image and/or an objectrecognition technique to identify the non-available parking areas and/orobjects or markers associated with the non-available parking areas.

In some implementations, the parking system can obtain one or morecoordinates (e.g., geolocation coordinates) of the non-demarcatedparking zone. The one or more coordinates can correspond to edges and/orcorners of the non-demarcated parking zone. Based on the coordinates,the parking system can calculate an area (e.g., an overall area) of thenon-demarcated parking zone (e.g., using any suitable geometriccalculation). In some implementations, the one or more coordinates cancorrespond to coordinates of streets and/or intersections that bound thenon-demarcated parking zone. In some implementations, the parking systemcan obtain the coordinates via a user input and/or during a calibrationphase when the parking system is configured to monitor thenon-demarcated parking zone. Using coordinates can be more accurate indetermining a shape of the non-demarcated parking zone (e.g., especiallyif the non-demarcated parking zone has an irregular shape).

Additionally, or alternatively, the parking system can determine thecoordinates based on coordinates of one or more markings (e.g., parkingsigns, no-parking signs at ends of the non-demarcated parking zone,and/or the like) identifying the non-demarcated parking zone. Forexample, the parking system can determine the dimensions of thenon-demarcated parking zone based on an image analysis (e.g., an objectrecognition analysis, a landscape analysis, and/or the like) of theimage stream. For example, an image analysis can be performed todetermine one or more dimensions of the non-demarcated parking zonebased on markings (e.g., parking signs or no parking signs) identifyingthe location of the non-demarcated parking zone. Accordingly, in suchcases, the parking system can automatically detect the location and/orsize of the non-demarcated parking zone without any user interaction.For example, using the image analysis and/or a determined location ofone or more of cameras A-D, a user might not need to provide the parkingsystem with coordinates of the non-demarcated parking zone, a locationof the non-demarcated parking zone, and/or the like to permit theparking system to determine or identify the coordinates of thenon-demarcated parking zone. In some implementations, during acalibration stage markers can be set (e.g., by a user) to indicateborders of the non-demarcated parking zone so that the parking systemcan identify the borders of the non-demarcated parking zone.

In some implementations, the parking system can use an image analysis toidentify one or more objects that designate “no parking” zones. Forexample, the parking system can identify a fire hydrant adjacent anon-demarcated parking zone along the side of the road. As such, theparking system can determine that an area within a threshold distance ofthe fire hydrant is not to be designated as part of the non-demarcatedparking zone, and thus not to be included in the overall area of thenon-demarcated parking zone. Additionally, or alternatively, the parkingsystem can identify rules associated the with non-demarcated parkingzone (e.g., “no parking on Sundays,” no parking between “5am and 9am,”and/or the like). Such rules can be received via a user device and/oridentified based on an image analysis of one or more signs posted nearthe non-demarcated parking zone. In some implementations, third partyplatforms can be accessed in accordance with the rules. For example, ifthere is a “no parking, snow plow zone” rule, the parking system canobtain information from a weather platform to determine whether therewas snow in the forecast or whether snow fell recently.

Referring to implementation 100 of FIG. 1B, the parking system candetermine from one or more of the above example techniques that thecapacity of the non-demarcated parking zone is five vehicles.Accordingly, as shown in FIG. 1B, at 12:00 on Sep. 26, 2018 the parkingsystem can determine that there is no parking availability in thenon-demarcated parking zone because the parking system can detect fivevehicles within the non-demarcated parking zone.

As shown in FIG. 1C, and by reference number 140, the parking system candetermine parking availability based on a number of vehicles in thenon-demarcated parking zone and/or a position or dimensions of thevehicles parked in the non-demarcated parking zone. For example, asshown in FIG. 1C, although, on Sep. 27, 2018 at 16:00, only threevehicles (shown as vehicle 1, vehicle 2, and vehicle 3) are parked inthe non-demarcated parking zone, the parking system can determine thatthere is no parking availability due to the size and/or position ofvehicle 2. In FIG. 1C, because vehicle 2 is larger than the averagevehicle and/or parked at an angle relative to the edge of thenon-demarcated parking zone (and, thus, taking up more length of thenon-demarcated parking zone than if the vehicle were parallel to theedge of the non-demarcated parking zone) there might not be enough spacebetween vehicle 2 and vehicle 1 or between vehicle 2 and vehicle 3.

In some implementations, the system can use vehicle information todetermine a distance between the vehicles. For example, the parkingsystem can identify make/model of the vehicle to determine the size ofthe vehicles in the image. Using the size of the vehicles for scale, theparking system can then determine a distance between the vehicles.Additionally, or alternatively, the parking system can use landmarking.For example, the parking system can use markings on a street, a locationof an object adjacent the non-demarcated parking zone (e.g., a tree, ahouse, a driveway, a sign, and/or the like) and known distances to theobject to estimate the distance between the vehicles based on theposition of the vehicles relative to the object.

In some implementations, the parking system can use a machine learningmodel, which can be referred to herein as object detection model, todetect vehicles in the non-demarcated parking zone. For example, parkingsystem can train the object detection model based on one or more objectdetection parameters associated with detecting a vehicle in an image,such as a shape of a vehicle, a type of a vehicle, a size of a vehicle,a motion of a vehicle, an outline of a vehicle, a resolution of an imagethat includes a vehicle, a contrast of an image that includes a vehicle,lighting of the image, brightness of the image, and/or the like. Theparking system can train the object detection model using historicaldata associated with detecting vehicles in the non-demarcated parkingzone according to the one or more object detection parameters. Using thehistorical data and the one or more object detection parameters asinputs to the object detection model, the parking system can detectvehicles in the non-demarcated parking zone to determine a number and/orposition of the vehicles in the non-demarcated parking zone.

In some implementations, the parking system can determine parkingavailability based on a determined distance between detected vehicles inthe non-demarcated parking zone. For example, using an image analysis ofthe image stream, the parking system can calculate a distance betweenvehicles in the non-demarcated parking zone. In such cases, if thedistance less a constant buffer to allow for room between the vehiclesis greater than an average dimension (e.g., a length or width) of avehicle or a known dimension of a particular vehicle, the parking systemcan determine that there is parking availability. On the other hand, ifthe distance less the constant buffer to allow for room between thevehicles is less than or equal to the average dimension (e.g., a lengthor width) or the known dimension of the particular vehicle, the parkingsystem can determine that there is no parking availability.

In some implementations, the parking system can determine whether thereis availability for a particular vehicle (or user of a particularvehicle) that is seeking to park in the non-demarcated parking zone. Forexample, if the parking system identifies that a vehicle is a relativelysmaller vehicle (e.g., a compact car), the parking system can determinethat there is parking availability for that particular vehicle. Forexample, the parking system, based on the smaller dimensions of theparticular vehicle, can determine that the vehicle can fit betweenvehicle 2 and vehicle 1 and/or between vehicle 2 and vehicle 3. On theother hand, if the parking system identifies that a particular vehicleis a relatively larger vehicle (e.g., a pickup truck or sport utilityvehicle (SUV)), the parking system can determine that there is noparking availability for the particular vehicle. In such cases, theparking system can identify the vehicle based on a user input, based onan identifier (e.g., a type, a model, a vehicle identification number(VIN), and/or the like) of the vehicle, based on the parking systembeing associated with the particular vehicle (e.g., installed within theparticular vehicle), and/or the like.

In some implementations, parking system can use a machine learningmodel, which can be referred to herein a parking availability model, todetermine the parking availability of a vehicle. For example, theparking system can train the parking availability model based on one ormore availability parameters associated with determining the parkingavailability, such as a size of a vehicle, a size of the non-demarcatedparking zone, a location of the vehicle, an estimated time of arrival ofthe vehicle, a type of the vehicle (e.g., make, model, utility, and/orthe like), and/or the like. The parking system can train the parkingavailability model using historical data associated with determining theparking availability of a non-demarcated parking zone for the vehicleaccording to the one or more availability parameters. Using thehistorical data and the one or more parameters as inputs to the machinelearning model, the parking system can determine the availability toindicate whether the vehicle can park (or a user can expect to park) inthe non-demarcated parking zone.

In some implementations, the parking availability can be represented bya probability that a vehicle would be able to park in the non-demarcatedparking zone upon arrival and/or that the non-demarcated parking zonewould include an open space to fit the vehicle. In some implementations,the probability is based on the positions of the vehicles in thenon-demarcated parking zone (and the corresponding distances between thevehicles), a size of the vehicle that is to park in the non-demarcatedparking zone, a type of the vehicle that is to park in thenon-demarcated parking zone, a location of the non-demarcated parkingzone, a location of the vehicle that is to park in the non-demarcatedparking zone, an estimated time of arrival of the vehicle that is topark in the non-demarcated parking zone, historical data associated withvehicles parking in the non-demarcated parking zone at a timecorresponding to the estimated time of arrival of the vehicle that is topark in the non-demarcated parking zone, and/or the like.

In some implementations, the parking system can store informationassociated with the non-demarcated parking zone in a data structure. Forexample, the parking system can store parking characteristics of thenon-demarcated parking zone in a data structure as historical data.Accordingly, the parking system can generate or build a data structureof historical data associated with vehicles parking in thenon-demarcated parking zone. As described herein, the data in the datastructure can be used to determine parking availability and/or predictparking availability for a particular time period.

Accordingly, a parking system can determine parking availability of thenon-demarcated parking zone of example implementation 100. In someimplementations, the parking system monitor and/or be associated withhundreds, thousands, or millions of non-demarcated parking zones and/orcapable of detecting hundreds, thousands, or millions of vehicles in thenon-demarcated parking zones. Accordingly, the parking system canmonitor such a large amount of data that it would not be possible forone or more human actors to monitor, comprehend, or determine a parkingavailability of the non-demarcated parking zones.

The parking system can use an image stream from one or more cameras todetermine the parking availability. The image stream can be analyzed todetermine the status of the non-demarcated parking zone, such as anumber of vehicles parked in the non-demarcated parking zone, respectivepositions of the vehicles parked in the non-demarcated parking zone,sizes of the vehicles parked in the non-demarcated parking zone,distances between the vehicles parked in the non-demarcated parkingzone, and/or the like. The parking system can estimate the parkingsystem based on the status of the non-demarcated parking zone, the sizeof the non-demarcated parking zone, and/or the size of a vehicle that isto park in the non-demarcated parking zone. As such, the parking systemcan identify and/or indicate parking availability to a user and/orvehicle (e.g., via a display of the vehicle and/or via a user device ofthe user). In this way, the user can conserve time, fuel, and/or usagecosts involved with identifying available parking in non-demarcatedparking zones.

In some implementations, the parking system can also have access todemarcated parking zones. In such cases, the parking system can provideinformation associated with parking availability in both the demarcatedparking zones and the non-demarcated parking zones. Accordingly, theparking system can indicate an optimal parking location for a vehicle oruser based on the determined availability of the demarcated and/ornon-demarcated parking zones. As such, the parking system can conservefuel, wear and tear on vehicles searching for any type of parking.

As indicated above, FIGS. 1A-1C are provided merely as an example. Otherexamples are possible and can differ from what was described with regardto FIGS. 1A-1C.

FIG. 2 is a diagram of an example implementation 200 described herein.In the example implementation 200 of FIG. 2, a user interface (e.g., agraphical user interface) on a display of a user device provides parkingavailability of non-demarcated parking zones (e.g., in real-time). Theuser interface of FIG. 2 can be associated with the parking system (oran application of the parking system) of example implementation 100. Forexample, the parking system of example implementation 100 can utilizethe user interface to provide parking availability to a user and/or to avehicle.

As shown in FIG. 2 and by reference number 210, the user interface canlist whether there is parking available within a plurality ofnon-demarcated parking zones and/or a plurality of demarcated parkingzones on the user interface. The listed non-demarcated parking zonesand/or demarcated parking zones can be non-demarcated parking zoneswithin a threshold distance of the user device. As shown by the checkmarks, in example implementation 200, there is available parking innon-demarcated parking zones at Main St. and 4^(th) Ave, at Main St. and5^(th) Ave, and State St. and 5^(th) Ave.

As further shown in FIG. 2, and by reference number 220, one of thenon-demarcated parking zones can be selected to provide more detail onthe parking availability. For example, Main St. and 5^(th) can beselected to show parking availability along Main St. Specifically,parking at 123 Main St. is indicated to be available on the west side ofMain St. (but not on the east side of Main St.).

Accordingly, in some implementations, the parking system can determineand/or provide an address of the non-demarcated parking zone and/or anaddress of an open space of the non-demarcated parking zone. The parkingsystem can determine the address based on mapping information and aposition of a camera of the parking system. As such, the parking system,can determine, from the image stream, an address of the non-demarcatedparking zone and/or an open space of the non-demarcated parking zone. Insome implementations, the parking system can determine the address byidentifying address information in the image stream. For example, theparking system can identify a street number of a building in the imageand determine the address of the open space based on the street numberof the building.

In some implementations, the parking system can provide navigationinformation to the user device to permit a user to navigate directly tothe open parking space of the non-demarcated parking zone. The parkingsystem can use any suitable navigation system to provide the navigationinformation to the user. Additionally, or alternatively, the navigationinformation can enable control of autonomous vehicles to arrive at thenon-demarcated parking zone based on the parking availability.Furthermore, the autonomous vehicle can be controlled to park in anavailable location of the non-demarcated parking zone.

As indicated above, FIG. 2 is provided merely as an example. Otherexamples are possible and can differ from what was described with regardto FIG. 2.

FIG. 3 is a diagram of an example implementation 300 described herein.In the example implementation 300 of FIG. 3, a user interface (e.g., agraphical user interface) on a display of a user device is shown toenable a user to search or determine parking availability of anon-demarcated parking zone near a particular location at a particulardate and/or time. Similar to the user interface of FIG. 2, the userinterface of FIG. 3 can be associated with the parking system (or anapplication of the parking system) of example implementation 100 of FIG.1.

As shown in FIG. 3, and by reference number 310, a user can enter alocation (e.g., an intersection (as shown) and/or an address), a date,and a time. The parking system, as described above, can estimate theprobability of the parking availability (the probability that parkingwill be available in non-demarcated parking zones near that location andat that time) based on historical data corresponding to that time and/ordate.

As further shown in FIG. 3, and by reference number 320, the userinterface shows the probability of available parking at non-demarcatedparking zones. For example, there is a 90% chance of available parkingat Main St. and 4^(th) Ave and a 5% chance of available parking at MainSt. and 6^(th) Ave. The probabilities can be calculated from historicaldata corresponding to the date and/or time. For example, because Sep.30, 2018 is a Sunday and there is a church at Main St. and 6^(th) Ave.,the parking system, over time, can determine that there is rarelyparking available in the non-demarcated parking zone at Main St. and6^(th) Ave. (because vehicles associated with church goers are in thenon-demarcated parking zone). As such, the parking system can indicatevia the user interface that there is a greater chance of finding parkingat Main St. and 4^(th) Ave. (or any of the other non-demarcated parkingzones).

Accordingly, using historical data associated with one or morenon-demarcated parking zones, the parking system can indicate aprobability that parking is available at the one or more non-demarcatedparking zones at a particular time and/or date. Accordingly, a userand/or vehicle can head straight toward the non-demarcated parking zonesthat have a higher probability of being available at those times and/ordates, thus conserving time and/or vehicle resources, as describedherein.

In some implementations, the probabilities that parking is available canbe updated in real-time. For example, as the requested time for therequested parking availability nears, the probability can be updatedperiodically (e.g., every minute, every hour, and/or the like) and/orbased on an event (e.g., a vehicle entering or leaving thenon-demarcated parking zone).

Accordingly, as described herein, the parking system described above canenable a user and/or a vehicle to identify parking availability of anon-demarcated parking zone. As such, the user and/or the vehicle canmore quickly determine where to park, thus saving time, fuel, and/orcosts associated with searching for available parking in one or morenon-demarcated parking zones.

As indicated above, FIG. 3 is provided merely as an example. Otherexamples are possible and can differ from what was described with regardto FIG. 3.

FIG. 4 is a diagram of an example environment 400 in which systemsand/or methods, described herein, can be implemented. As shown in FIG.4, environment 400 can include a user device 410, a parking system 420hosted within a cloud computing environment 415, a parking monitor 430,and a network 440. Devices of environment 400 can interconnect via wiredconnections, wireless connections, or a combination of wired andwireless connections.

User device 410 includes one or more devices capable of receiving,generating, storing, processing, and/or providing information associatedwith identifying and/or indicating parking availability of one or morenon-demarcated parking zones. For example, user device 410 can include acommunication and/or computing device, such as a mobile phone (e.g., asmart phone, a radiotelephone, etc.), a laptop computer, a tabletcomputer, a handheld computer, a gaming device, a wearable communicationdevice (e.g., a smart wristwatch, a pair of smart eyeglasses, etc.), acontrol console of a vehicle, or a similar type of device.

Parking system 420 includes one or more computing resources assigned todetermine and/or provide parking availability of one or morenon-demarcated parking zones. For example, parking system 420 can be aplatform implemented by cloud computing environment 415 that can receiveand/or analyze an image stream of a non-demarcated parking zone,determine a capacity of the non-demarcated parking zone, determine anumber of vehicles and/or a position of the vehicles in thenon-demarcated parking zone, and/or determine the parking availabilityof the non-demarcated parking zone based on the capacity and/or thenumber and/or the position of the vehicles in the non-demarcated parkingzone. In some implementations, parking system 420 is implemented bycomputing resources 425 of cloud computing environment 415.

Parking system 420 can include a server device or a group of serverdevices. In some implementations, parking system 420 can be hosted incloud computing environment 415. Notably, while implementationsdescribed herein describe parking system 420 as being hosted in cloudcomputing environment 415, in some implementations, parking system 420might not be cloud-based or can be partially cloud-based.

Cloud computing environment 415 includes an environment that deliverscomputing as a service, whereby shared resources, services, etc. can beprovided to user device 410 and/or parking monitor 430. Cloud computingenvironment 415 can provide computation, software, data access, storage,and/or other services that do not require end-user knowledge of aphysical location and configuration of a system and/or a device thatdelivers the services. As shown, cloud computing environment 415 caninclude parking system 420 and computing resource 425.

Computing resource 425 includes one or more personal computers,workstation computers, server devices, or another type of computationand/or communication device. In some implementations, computing resource425 can host parking system 420. The cloud resources can include computeinstances executing in computing resource 425, storage devices providedin computing resource 425, data transfer devices provided by computingresource 425, etc. In some implementations, computing resource 425 cancommunicate with other computing resources 425 via wired connections,wireless connections, or a combination of wired and wirelessconnections.

As further shown in FIG. 4, computing resource 425 can include a groupof cloud resources, such as one or more applications (“APPs”) 425-1, oneor more virtual machines (“VMs”) 425-2, virtualized storage (“VSs”)425-3, one or more hypervisors (“HYPs”) 425-4, or the like.

Application 425-1 includes one or more software applications that can beprovided to or accessed by user device 410. Application 425-1 caneliminate a need to install and execute the software applications onuser device 410. For example, application 425-1 can include softwareassociated with parking system 420 and/or any other software capable ofbeing provided via cloud computing environment 415. In someimplementations, one application 425-1 can send/receive informationto/from one or more other applications 425-1, via virtual machine 425-2.

Virtual machine 425-2 includes a software implementation of a machine(e.g., a computer) that executes programs like a physical machine.Virtual machine 425-2 can be either a system virtual machine or aprocess virtual machine, depending upon use and degree of correspondenceto any real machine by virtual machine 425-2. A system virtual machinecan provide a complete system platform that supports execution of acomplete operating system (“OS”). A process virtual machine can executea single program and can support a single process. In someimplementations, virtual machine 425-2 can execute on behalf of a user(e.g., user device 410), and can manage infrastructure of cloudcomputing environment 415, such as data management, synchronization, orlong-duration data transfers.

Virtualized storage 425-3 includes one or more storage systems and/orone or more devices that use virtualization techniques within thestorage systems or devices of computing resource 425. In someimplementations, within the context of a storage system, types ofvirtualizations can include block virtualization and filevirtualization. Block virtualization can refer to abstraction (orseparation) of logical storage from physical storage so that the storagesystem can be accessed without regard to physical storage orheterogeneous structure. The separation can permit administrators of thestorage system flexibility in how the administrators manage storage forend users. File virtualization can eliminate dependencies between dataaccessed at a file level and a location where files are physicallystored. This can enable optimization of storage use, serverconsolidation, and/or performance of non-disruptive file migrations.

Hypervisor 425-4 provides hardware virtualization techniques that allowmultiple operating systems (e.g., “guest operating systems”) to executeconcurrently on a host computer, such as computing resource 425.Hypervisor 425-4 can present a virtual operating platform to the guestoperating systems and can manage the execution of the guest operatingsystems. Multiple instances of a variety of operating systems can sharevirtualized hardware resources.

Parking monitor 430 includes a system of one or more monitoring devicesfor monitoring a non-demarcated parking zone, determiningcharacteristics of the non-demarcated parking zone, and/or providinginformation associated with the non-demarcated parking zone. Forexample, parking monitor 430 can include one or more cameras, sensors(e.g., radar sensors, motion sensors, pressure sensors, audio sensors,temperature sensors, and/or the like), security devices, and/or thelike. Parking monitor 430 can provide, to parking system 420, imagesfrom cameras, sensor data from sensors, security information fromsecurity devices, and/or any other information related to anon-demarcated parking zone from any other monitoring devices.

Network 440 includes one or more wired and/or wireless networks. Forexample, network 440 can include a cellular network (e.g., a long-termevolution (LTE) network, a code division multiple access (CDMA) network,a 3G network, a 4G network, a 5G network, another type of nextgeneration network, etc.), a public land mobile network (PLMN), a localarea network (LAN), a wide area network (WAN), a metropolitan areanetwork (MAN), a telephone network (e.g., the Public Switched TelephoneNetwork (PSTN)), a private network, an ad hoc network, an intranet, theInternet, a fiber optic-based network, a cloud computing network, or thelike, and/or a combination of these or other types of networks.

The number and arrangement of devices and networks shown in FIG. 4 areprovided as an example. In practice, there can be additional devicesand/or networks, fewer devices and/or networks, different devices and/ornetworks, or differently arranged devices and/or networks than thoseshown in FIG. 4. Furthermore, two or more devices shown in FIG. 4 can beimplemented within a single device, or a single device shown in FIG. 4can be implemented as multiple, distributed devices. Additionally, oralternatively, a set of devices (e.g., one or more devices) ofenvironment 400 can perform one or more functions described as beingperformed by another set of devices of environment 400.

FIG. 5 is a diagram of example components of a device 500. Device 500can correspond user device 410 and parking monitor 430. In someimplementations, user device 410 and/or parking monitor 430 can includeone or more devices 500 and/or one or more components of device 500. Asshown in FIG. 3, device 500 can include a bus 510, a processor 520, amemory 530, a storage component 540, an input component 550, an outputcomponent 560, and a communication interface 570.

Bus 510 includes a component that permits communication among thecomponents of device 500. Processor 520 is implemented in hardware,firmware, or a combination of hardware and software. Processor 520 is acentral processing unit (CPU), a graphics processing unit (GPU), anaccelerated processing unit (APU), a microprocessor, a microcontroller,a digital signal processor (DSP), a field-programmable gate array(FPGA), an application-specific integrated circuit (ASIC), or anothertype of processing component. In some implementations, processor 520includes one or more processors capable of being programmed to perform afunction. Memory 530 includes a random-access memory (RAM), a read onlymemory (ROM), and/or another type of dynamic or static storage device(e.g., a flash memory, a magnetic memory, and/or an optical memory) thatstores information and/or instructions for use by processor 520.

Storage component 540 stores information and/or software related to theoperation and use of device 500. For example, storage component 540 caninclude a hard disk (e.g., a magnetic disk, an optical disk, amagneto-optic disk, and/or a solid-state disk), a compact disc (CD), adigital versatile disc (DVD), a floppy disk, a cartridge, a magnetictape, and/or another type of non-transitory computer-readable medium,along with a corresponding drive.

Input component 550 includes a component that permits device 500 toreceive information, such as via user input (e.g., a touch screendisplay, a keyboard, a keypad, a mouse, a button, a switch, and/or amicrophone). Additionally, or alternatively, input component 550 caninclude a sensor for sensing information (e.g., a global positioningsystem (GPS) component, an accelerometer, a gyroscope, and/or anactuator). Output component 560 includes a component that providesoutput information from device 500 (e.g., a display, a speaker, and/orone or more light-emitting diodes (LEDs)).

Communication interface 570 includes a transceiver-like component (e.g.,a transceiver and/or a separate receiver and transmitter) that enablesdevice 500 to communicate with other devices, such as via a wiredconnection, a wireless connection, or a combination of wired andwireless connections. Communication interface 570 can permit device 500to receive information from another device and/or provide information toanother device. For example, communication interface 570 can include anEthernet interface, an optical interface, a coaxial interface, aninfrared interface, a radio frequency (RF) interface, a universal serialbus (USB) interface, a wireless local area network interface, a cellularnetwork interface, or the like.

Device 500 can perform one or more processes described herein. Device500 can perform these processes based on processor 520 executingsoftware instructions stored by a non-transitory computer-readablemedium, such as memory 530 and/or storage component 540. Acomputer-readable medium is defined herein as a non-transitory memorydevice. A memory device includes memory space within a single physicalstorage device or memory space spread across multiple physical storagedevices.

Software instructions can be read into memory 530 and/or storagecomponent 540 from another computer-readable medium or from anotherdevice via communication interface 570. When executed, softwareinstructions stored in memory 530 and/or storage component 540 can causeprocessor 520 to perform one or more processes described herein.Additionally, or alternatively, hardwired circuitry can be used in placeof or in combination with software instructions to perform one or moreprocesses described herein. Thus, implementations described herein arenot limited to any specific combination of hardware circuitry andsoftware.

The number and arrangement of components shown in FIG. 5 are provided asan example. In practice, device 500 can include additional components,fewer components, different components, or differently arrangedcomponents than those shown in FIG. 5. Additionally, or alternatively, aset of components (e.g., one or more components) of device 500 canperform one or more functions described as being performed by anotherset of components of device 500.

FIG. 6 is a flow chart of an example process 600 associated with aparking availability monitor for a non-demarcated parking zone. In someimplementations, one or more process blocks of FIG. 6 can be performedby a parking system (e.g., parking system 420). In some implementations,one or more process blocks of FIG. 6 can be performed by another deviceor a group of devices separate from or including the parking system,such as a user device (e.g., user device 410), a parking monitor (e.g.,parking monitor 430), and/or the like.

As shown in FIG. 6, process 600 can include receiving an image stream ofa non-demarcated parking zone (block 610). For example, the parkingsystem, (e.g., using computing resource 425, processor 520, memory 530,input component 550, communication interface 570, and/or the like) canreceive an image stream of a non-demarcated parking zone, as describedabove.

As further shown in FIG. 6, process 600 can include identifyingdimensions of the non-demarcated parking zone (block 620). For example,the parking system, (e.g., using computing resource 425, processor 520,memory 530, and/or the like) can identify dimensions of thenon-demarcated parking zone, as described above.

As further shown in FIG. 6, process 600 can include determining anoverall area of the non-demarcated parking zone based on the dimensionsof the non-demarcated parking zone (block 630). For example, the parkingsystem, (e.g., using computing resource 425, processor 520, memory 530,and/or the like) can determine an overall area of the non-demarcatedparking zone based on the dimensions of the non-demarcated parking zone,as described above.

As further shown in FIG. 6, process 600 can include calculating acapacity of the non-demarcated parking zone based on the dimensions ofthe overall area and predetermined vehicle dimensions (block 640). Forexample, the parking system, (e.g., using computing resource 425,processor 520, memory 530, and/or the like) can calculate a capacity ofthe non-demarcated parking zone based on the dimensions of the overallarea and predetermined vehicle dimensions, as described above.

As further shown in FIG. 6, process 600 can include determining a numberof vehicles parked in the non-demarcated parking zone based on the imagestream and an object detection model, wherein the object detection modelis configured to detect vehicles in the image stream that are parked inthe non-demarcated parking zone (block 650). For example, the parkingsystem, (e.g., using computing resource 425, processor 520, memory 530,and/or the like) can determine a number of vehicles parked in thenon-demarcated parking zone based on the image stream and an objectdetection model, as described above. In some implementations, the objectdetection model is configured to detect vehicles in the image streamthat are parked in the non-demarcated parking zone.

As further shown in FIG. 6, process 600 can include determining aparking availability of the non-demarcated parking zone based on thenumber of vehicles parked in the non-demarcated parking zone and thecapacity, wherein the parking availability indicates whether a firstvehicle can park in the non-demarcated parking zone (block 660). Forexample, the parking system, (e.g., using computing resource 425,processor 520, memory 530, and/or the like) can determine a parkingavailability of the non-demarcated parking zone based on the number ofvehicles parked in the non-demarcated parking zone and the capacity, asdescribed above. In some implementations, the parking availabilityindicates whether a first vehicle can park in the non-demarcated parkingzone.

As further shown in FIG. 6, process 600 can include performing an actionassociated with there being parking availability (block 670). Forexample, the parking system, (e.g., using computing resource 425,processor 520, memory 530, output component 560, communication interface570, and/or the like) can perform an action associated with there beingparking availability, as described above.

As further shown in FIG. 6, process 600 can include performing an actionassociated with there not being parking availability (block 680). Forexample, the parking system, (e.g., using computing resource 425,processor 520, memory 530, output component 560, communication interface570, and/or the like) can perform an action associated with there notbeing parking availability, as described above.

Process 600 can include additional implementations, such as any singleimplementation or any combination of implementations described belowand/or in connection with one or more other processes describedelsewhere herein.

In some implementations, the parking system can analyze the image streamto determine respective positions of the number of vehicles parkedwithin the non-demarcated parking zone and determine the parkingavailability based on a probability that the non-demarcated parking zoneincludes an open space to fit the first vehicle. In someimplementations, the probability that the non-demarcated parking zoneincludes an open space to fit the first vehicle is determined based onbased on the respective positions of the number of vehicles within anddimensions of the first vehicle.

In some implementations, the parking system can receive informationidentifying a time period during which the first vehicle is to park inthe non-demarcated parking zone, analyze historical data associated withthe parking availability of the non-demarcated parking zone during thetime period, and estimate the parking availability for the time periodbased on the historical data, the number of vehicles parked in thenon-demarcated parking zone, and the capacity.

In some implementations, the parking availability is determined using amachine learning model. In some implementations, the machine learningmodel is trained based on historical data associated with the parkingavailability of the non-demarcated parking zone and one or moreparameters associated with the first vehicle. In some implementations,the one or more parameters include at least one of: a location of thefirst vehicle, an estimated amount of time of arrival of the firstvehicle, a dimension of the first vehicle, or a type of the firstvehicle.

In some implementations, the parking system can determine respectivedimensions of a plurality of vehicles that have parked in thenon-demarcated parking zone and calculate the predetermined vehicledimensions based on an average of the respective dimensions of theplurality of vehicles that have parked in the non-demarcated parkingzone.

In some implementations, the parking system, when performing the action,can, based on the parking availability indicating that the first vehiclecan park in the non-demarcated parking zone, determine locationinformation associated with an available parking space in thenon-demarcated parking zone and provide the location information to auser device.

In some implementations, the parking system, when performing the action,can store the parking availability a data structure, present the parkingavailability in real-time on a display of a user device, or providenavigation information to the non-demarcated parking zone to a userdevice. In some implementations, the parking availability can beobtained from the data structure to determine a future parkingavailability for a time period.

Although FIG. 6 shows example blocks of process 600, in someimplementations, process 600 can include additional blocks, fewerblocks, different blocks, or differently arranged blocks than thosedepicted in FIG. 6. Additionally, or alternatively, two or more of theblocks of process 600 can be performed in parallel.

The foregoing disclosure provides illustration and description but isnot intended to be exhaustive or to limit the implementations to theprecise form disclosed. Modifications and variations are possible inlight of the above disclosure or can be acquired from practice of theimplementations.

As used herein, the term component is intended to be broadly construedas hardware, firmware, or a combination of hardware and software.

Some implementations are described herein in connection with thresholds.As used herein, satisfying a threshold can refer to a value beinggreater than the threshold, more than the threshold, higher than thethreshold, greater than or equal to the threshold, less than thethreshold, fewer than the threshold, lower than the threshold, less thanor equal to the threshold, equal to the threshold, or the like.

Certain user interfaces have been described herein and/or shown in thefigures. A user interface can include a graphical user interface, anon-graphical user interface, a text-based user interface, or the like.A user interface can provide information for display. In someimplementations, a user can interact with the information, such as byproviding input via an input component of a device that provides theuser interface for display. In some implementations, a user interfacecan be configurable by a device and/or a user (e.g., a user can changethe size of the user interface, information provided via the userinterface, a position of information provided via the user interface,etc.). Additionally, or alternatively, a user interface can bepre-configured to a standard configuration, a specific configurationbased on a type of device on which the user interface is displayed,and/or a set of configurations based on capabilities and/orspecifications associated with a device on which the user interface isdisplayed.

To the extent the aforementioned implementations collect, store, oremploy personal information of individuals, it should be understood thatsuch information shall be used in accordance with all applicable lawsconcerning protection of personal information. Additionally, thecollection, storage, and use of such information can be subject toconsent of the individual to such activity, for example, through wellknown “opt-in” or “opt-out” processes as can be appropriate for thesituation and type of information. Storage and use of personalinformation can be in an appropriately secure manner reflective of thetype of information, for example, through various encryption andanonymization techniques for particularly sensitive information.

It will be apparent that systems and/or methods, described herein, canbe implemented in different forms of hardware, firmware, or acombination of hardware and software. The actual specialized controlhardware or software code used to implement these systems and/or methodsis not limiting of the implementations. Thus, the operation and behaviorof the systems and/or methods were described herein without reference tospecific software code—it being understood that software and hardwarecan be designed to implement the systems and/or methods based on thedescription herein.

Even though particular combinations of features are recited in theclaims and/or disclosed in the specification, these combinations are notintended to limit the disclosure of possible implementations. In fact,many of these features can be combined in ways not specifically recitedin the claims and/or disclosed in the specification. Although eachdependent claim listed below can directly depend on only one claim, thedisclosure of possible implementations includes each dependent claim incombination with every other claim in the claim set.

No element, act, or instruction used herein should be construed ascritical or essential unless explicitly described as such. Also, as usedherein, the articles “a” and “an” are intended to include one or moreitems and can be used interchangeably with “one or more.” Furthermore,as used herein, the term “set” is intended to include one or more items(e.g., related items, unrelated items, a combination of related andunrelated items, etc.), and can be used interchangeably with “one ormore.” Where only one item is intended, the term “one” or similarlanguage is used. Also, as used herein, the terms “has,” “have,”“having,” or the like are intended to be open-ended terms. Further, thephrase “based on” is intended to mean “based, at least in part, on”unless explicitly stated otherwise.

1. A method, comprising: calculating, by a device, a capacity of anon-demarcated parking zone based on dimensions of an overall area ofthe non-demarcated parking zone and predetermined vehicle dimensions;determining, by the device, a quantity of vehicles parked in thenon-demarcated parking zone based on an image stream and an objectdetection model; determining, by the device, a parking availability ofthe non-demarcated parking zone based on the quantity of vehicles parkedin the non-demarcated parking zone and the capacity; and performing, bythe device, an action related to the non-demarcated parking zone basedon the parking availability.
 2. The method of claim 1, wherein theparking availability indicates whether a first vehicle can park in thenon-demarcated parking zone.
 3. The method of claim 1, whereinperforming the action comprises at least one of: storing the parkingavailability in a data structure, wherein the parking availability canbe obtained from the data structure to determine a future parkingavailability for a time period; providing information associated withthe parking availability to a user device; or providing navigationinformation to the non-demarcated parking zone to a user device.
 4. Themethod of claim 1, further comprising: analyzing the image stream todetermine respective positions of the quantity of vehicles parked withinthe non-demarcated parking zone; and wherein determining the parkingavailability further includes: determining the parking availabilitybased on a probability that the non-demarcated parking zone includes anopen space to fit a first vehicle, wherein the probability that thenon-demarcated parking zone includes an open space to fit the firstvehicle is determined based on based on the respective positions of thequantity of vehicles within the non-demarcated parking zone anddimensions of the first vehicle.
 5. The method of claim 1, furthercomprising: calculating a probability that one or more parking spots areavailable to receive one or more vehicles, the probability beingcalculated based upon at least one of: occupancy status of the one ormore parking spots; a presence of a person within a threshold range ofthe one or more parking spots; or a presence of a vehicle appearing toenter the one or more parking spots.
 6. The method of claim 5, whereincalculating the probability comprises: utilizing a probability scoringsystem based on at least one of: characteristics associated with the oneor more parking spots, or characteristics associated with the one ormore vehicles.
 7. The method of claim 1, wherein the parkingavailability is determined using a machine learning model, wherein themachine learning model is trained based on historical data associatedwith the parking availability of the non-demarcated parking zone and oneor more parameters associated with a first vehicle, and wherein the oneor more parameters include at least one of: a location of the firstvehicle, an estimated time of arrival of the first vehicle, a dimensionof the first vehicle, or a type of the first vehicle.
 8. A device,comprising: one or more memories; and one or more processorscommunicatively coupled to the one or more memories, configured to:determine a capacity of a non-demarcated parking zone based ondimensions of an overall area of the non-demarcated parking zone andpredetermined vehicle dimensions; determine a quantity of vehiclesparked in the non-demarcated parking zone based on an image stream andan object detection model; determine a parking availability of thenon-demarcated parking zone based on the quantity of vehicles parked inthe non-demarcated parking zone and the capacity, wherein the parkingavailability indicates whether a first vehicle can park in thenon-demarcated parking zone; and perform an action related to thenon-demarcated parking zone based on the parking availability.
 9. Thedevice of claim 8, wherein the object detection model is configured todetect vehicles in the image stream that are parked in thenon-demarcated parking zone.
 10. The device of claim 9, wherein theobject detection model is trained based on one or more object detectionparameters associated with detecting vehicles in the image stream. 11.The device of claim 8, wherein the one or more processors are furtherconfigured to: analyze the image stream to determine respectivepositions of the quantity of vehicles parked within the non-demarcatedparking zone; and determine the parking availability based on aprobability that the non-demarcated parking zone includes an open spaceto fit a first vehicle, wherein the probability that the non-demarcatedparking zone includes an open space to fit the first vehicle isdetermined based on based on the respective positions of the quantity ofvehicles within and dimensions of the first vehicle.
 12. The device ofclaim 8, wherein the one or more processors are further configured to:calculate a probability that one or more parking spots can be availableto receive one or more vehicles, the probability being calculated basedupon at least one of: occupancy status of the one or more parking spots;a presence of a person within a threshold range of the one or moreparking spots; or a presence of a vehicle appearing to enter the one ormore parking spots.
 13. The device of claim 12, wherein the one or moreprocessors, when calculating the probability, are configured to: utilizea probability scoring system based on characteristics associated withthe one or more parking spots and/or characteristics associated with theone or more vehicles.
 14. The device of claim 8, wherein the parkingavailability is determined using a machine learning model, wherein themachine learning model is trained based on historical data associatedwith the parking availability of the non-demarcated parking zone and oneor more parameters associated with a first vehicle, and wherein the oneor more parameters include at least one of: a location of the firstvehicle, an estimated amount of time of arrival of the first vehicle, adimension of the first vehicle, or a type of the first vehicle.
 15. Anon-transitory computer-readable medium storing instructions, theinstructions comprising: one or more instructions that, when executed byone or more processors, cause the one or more processors to: calculate acapacity of a non-demarcated parking zone based on dimensions of anoverall area of the non-demarcated parking zone and predeterminedvehicle dimensions; determine a quantity of vehicles parked in thenon-demarcated parking zone based on an image stream and a machinelearning model; determine a parking availability of the non-demarcatedparking zone based on the quantity of vehicles parked in thenon-demarcated parking zone and the capacity; and perform an actionrelated to the non-demarcated parking zone based on the parkingavailability.
 16. The non-transitory computer-readable medium of claim15, wherein the machine learning model is configured to detect vehiclesin the image stream that are parked in the non-demarcated parking zone.17. The non-transitory computer-readable medium of claim 15, wherein theone or more instructions, that cause the one or more processors toperform the action, cause the one or more processors to at least one of:determine, based on the parking availability indicating that the firstvehicle can park in the non-demarcated parking zone, locationinformation associated with an available parking space in thenon-demarcated parking zone; or provide the location information to auser device.
 18. The non-transitory computer-readable medium of claim15, wherein the one or more instructions, when executed by the one ormore processors, further cause the one or more processors to: analyzethe image stream to determine respective positions of the quantity ofvehicles parked within the non-demarcated parking zone; and determinethe parking availability based on a probability that the non-demarcatedparking zone includes an open space to fit a first vehicle, wherein theprobability that the non-demarcated parking zone includes an open spaceto fit the first vehicle is determined based on based on the respectivepositions of the quantity of vehicles within and dimensions of the firstvehicle.
 19. The non-transitory computer-readable medium of claim 15,wherein the one or more instructions, when executed by the one or moreprocessors, further cause the one or more processors to: calculate aprobability that one or more parking spots can be available to receiveone or more vehicles, the probability being calculated based upon atleast one of: occupancy status of the one or more parking spots; apresence of a person within a threshold range of the one or more parkingspots; or a presence of a vehicle appearing to enter the one or moreparking spots.
 20. The non-transitory computer-readable medium of claim15, wherein the machine learning model is trained based on historicaldata associated with the parking availability of the non-demarcatedparking zone and one or more parameters associated with a first vehicle,and wherein the one or more parameters include at least one of: alocation of the first vehicle, an estimated amount of time of arrival ofthe first vehicle, a dimension of the first vehicle, or a type of thefirst vehicle.